The present invention relates to technical solution of grid data processing, and in particularly, to a method and apparatus for processing grid data according to information about insulator flashover.
It is a common phenomenon in a grid that tripping of switch occurs in a substation, and the time to re-close the switch after tripping is very short, usually in milliseconds, thus an external user usually will not sense the power failure, however, trip-up record is one kind of important grid data. Since tripping occurs frequently, the resultant trip-up records are usually of massive volume. For example, for a city-scale substation, trip-up records per day will be as many as several hundreds of thousands of pieces. Therefore, how to accurately analyze grid data having massive volume of trip-up records becomes a challenge in electric power field.
Typically, tripping events are recorded in grid data, especially in a SCADA system. There are many causes for tripping, such as overloaded line, aging facilities, flashover of insulator, etc., in which 70% of the tripping events are caused by insulator flashover. Many meaningful tripping failure records will be mixed among a vast number of tripping events caused by flashover, thus, efficient analysis could not be performed on tripping records, which, in turn, becomes a significant interference and seriously hinders analysis on grid data.
Currently, determining causes of tripping events is performed manually, for example, by manually checking other operation status recording system to see whether there is line overload at the time at which tripping occurs, or by manually collecting statistics about lines where tripping occurs frequently, and then checking whether there is aging facility, whether insulator flashover has occurred, etc. In electric power field, since the amount of data of trip-up records is very huge, and efficiency of existing manual checking is very low, there is an urgent need to provide an efficient technique for determining trip-up records caused by flashover.
Therefore, there is still room to improve existing grid data processing solution, and there is a need to efficiently determine trip-up records caused by insulator flashover from grid data records, thereby providing effective assistance to subsequently improve grid data analysis.